Triple

T1540966
Position Surface form Disambiguated ID Type / Status
Subject UNASUL E32863 entity
Predicate headquartersLocation P62 FINISHED
Object Quito E8614 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Quito | Statement: [UNASUL, headquartersLocation, Quito]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Quito
Context triple: [UNASUL, headquartersLocation, Quito]
  • A. Quito chosen
    Quito is the high-altitude Andean city that serves as Ecuador’s political and cultural center, renowned for its well-preserved colonial historic center and dramatic mountain setting.
  • B. Guayaquil
    Guayaquil is a major Pacific port city in southwestern Ecuador and the country’s principal commercial and industrial center.
  • C. Bogotá
    Bogotá is the high-altitude capital and largest city of Colombia, known as a major political, economic, and cultural center in South America.
  • D. La Paz
    La Paz is the administrative capital and one of the major cities of Bolivia, known for its dramatic setting in a deep valley of the Andes at one of the highest elevations of any capital city in the world.
  • E. La Paz
    La Paz is the capital city of Baja California Sur in Mexico, known for its coastal location on the Gulf of California, marine biodiversity, and laid-back seaside atmosphere.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a885ed29088190a3c2d5a3d100c16e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa61faaaa4819089120e25f4bcb0f6 completed March 6, 2026, 5:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69adc98b2b0081909d10b22d59c5e653 completed March 8, 2026, 7:10 p.m.
Created at: March 4, 2026, 7:26 p.m.